Diagnosis of covid-19 using CNN algorithm

Now a days COVID 19 is rapidly spreading everywhere. It is one of the deadliest viruses within the global. The pandemic caused by the corona virus is huge and the world goes under more struggle and also many of the people were died due to this. So that the doctor has to diagnosis the virus as quick as possible to recover the patient from the virus. Currently for diagnosing the corona virus ANN algorithm is used. This makes more time to diagnosis the virus from the patient. The ANN algorithm includes the process, first we have to take the CT image of chest region of the patient. Next, we have to analysis the CT image is there any new type of virus is present are not with the help of healthy patient CT image. This takes more time to analysis the corona virus. For reducing that time consumption, we are going for CNN algorithm (Convolution Neural Network). This reduces the time of diagnosing the virus from the patient. This algorithm is trained to find the corona virus from the CT image of the patient.

[1]  Prabira Kumar Sethy,et al.  Detection of Coronavirus Disease (COVID-19) Based on Deep Features , 2020 .

[2]  Wei Qian,et al.  Clinical and computed tomographic (CT) images characteristics in the patients with COVID-19 infection: What should radiologists need to know? , 2020, Journal of X-ray science and technology.

[3]  Asif Iqbal Khan,et al.  CoroNet: A deep neural network for detection and diagnosis of COVID-19 from chest x-ray images , 2020, Computer Methods and Programs in Biomedicine.

[4]  Daniel S. Kermany,et al.  Identifying Medical Diagnoses and Treatable Diseases by Image-Based Deep Learning , 2018, Cell.

[5]  S. Palanivel Rajan Review and investigations on future research directions of mobile based telecare system for cardiac surveillance , 2015 .

[6]  Fan Lin,et al.  CT Imaging and Differential Diagnosis of COVID-19 , 2020, Canadian Association of Radiologists journal = Journal l'Association canadienne des radiologistes.

[7]  Alexander Wong,et al.  COVID-Net: a tailored deep convolutional neural network design for detection of COVID-19 cases from chest X-ray images , 2020, Scientific reports.

[8]  R. Praveen Kumar,et al.  Computation of the fluid flow and the temperature field by finite element modeling , 2018, Cluster Computing.

[9]  K. Kaarthik,et al.  An Efficient Architecture Implemented to Reduce Area in VLSI Adders , 2017 .

[10]  Mamun Bin Ibne Reaz,et al.  Can AI Help in Screening Viral and COVID-19 Pneumonia? , 2020, IEEE Access.

[11]  Bo Xu,et al.  A deep learning algorithm using CT images to screen for Corona virus disease (COVID-19) , 2020, European Radiology.

[12]  Abolfazl Attar,et al.  A modified deep convolutional neural network for detecting COVID-19 and pneumonia from chest X-ray images based on the concatenation of Xception and ResNet50V2 , 2020, Informatics in Medicine Unlocked.

[13]  Mohamed Abd Elaziz,et al.  New machine learning method for image-based diagnosis of COVID-19 , 2020, PloS one.

[14]  Michael H. Goldbaum,et al.  Large Dataset of Labeled Optical Coherence Tomography (OCT) and Chest X-Ray Images , 2018 .

[15]  Ioannis D. Apostolopoulos,et al.  Covid-19: automatic detection from X-ray images utilizing transfer learning with convolutional neural networks , 2020, Physical and Engineering Sciences in Medicine.

[16]  Ting Yu,et al.  Epidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: a descriptive study , 2020, The Lancet.

[17]  U. Rajendra Acharya,et al.  Automated detection of COVID-19 cases using deep neural networks with X-ray images , 2020, Computers in Biology and Medicine.